Modeling, Dynamics and Control approaches for Modern Robotics

著者名：Taher Azar, Ahmad (EDT)/Fekik, Arezki (EDT)

Academic Press（2026/02/06発売）

• 言語：ENG
• ISBN：9780443301063
• eISBN：9780443301070

Description

Modeling, Dynamics and Control approaches for Modern Robotics explores and investigates various theoretical and practical principles related to modeling, dynamics, and control in robotics. The objective is to enhance the understanding and development of robotic systems by applying these principles. Through accurate representations of robot kinematics and dynamics, researchers aim to effectively analyze and predict robot behavior. This title focuses on designing algorithms and control strategies for precise and efficient robotic system management.Additionally, the book delves into sensory feedback and perception systems for robots, advancements in autonomous vehicles, industrial automation, humanoid robots, and medical robotics, showcasing the integration of technology and computing power in modern applications. The study of control approaches and the development of optimized performance schemes are highlighted, demonstrating the significance of stability and adaptive response in changing environments. This comprehensive examination underscores the evolution and complexity of robotic systems, emphasizing their growing role in various sectors.- Includes advanced methodologies for various robotics control issues- Deals with recent research problems in the areas of robotics, control systems, dynamical modeling, and optimization- Presents advanced techniques of motion control and path planning of mobile robots- Covers chapters that are lucidly illustrated with numerical examples and simulations- Discusses details of applications and future research areas

Table of Contents

1. Control Systems Principles2. Kinematics and Dynamics3. Sensors and Actuators control4. System Architectures5. Trajectory planning of a mobile robot with obstacle avoidance using conventional methods and heuristic methods6. Hardware Implementation of a Neuro-fuzzy Controller for robotic Manipulators7. Computed Torque Control of the PUMA 560 Robot8. Developing Medical Robotics with AI-Enhanced Biosensors9. Visualisation of 3D trajectory control of drones using computer aided modelling.10. Proportional-Derivative control for nonlinear robot dynamics using adaptive finite-time approach11. Disturbance observer based sliding mode control with fixed-time convergence for perturbed robotic manipulators12. Drone-based image processing to detect palm tree diseases13. Model-Based Control Strategies14. Optimal Control Approaches15. Robust Control Strategies for Robotics16. Advances in Medical Robotics17. Explainable AI for Robotics18. Reinforcement Learning for Robotics19. Deep Reinforcement Learning for Robotics20. Ethics for Robotics